Overview

Dataset statistics

Number of variables7
Number of observations1353
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory76.8 KiB
Average record size in memory58.1 B

Variable types

Numeric2
Categorical2
Text1
DateTime2

Dataset

Description한국나노기술원에서 제공하는 예약장비 정보입니다.* 대관 상세 정보 :한국나노기술원_대관 예약실 현황(https://www.data.go.kr/data/15037652/fileData.do)한국나노기술원_대관 예약신청 현황(https://www.data.go.kr/data/15037654/fileData.do)한국나노기술원_대관 시설 정보(https://www.data.go.kr/data/15037655/fileData.do)
Author한국나노기술원
URLhttps://www.data.go.kr/data/15037653/fileData.do

Alerts

신청장비명 is highly imbalanced (51.8%)Imbalance
대관신청번호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 15:57:55.490180
Analysis finished2023-12-12 15:57:57.136504
Duration1.65 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

대관신청번호
Real number (ℝ)

UNIQUE 

Distinct1353
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1001.8721
Minimum227
Maximum1739
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size12.0 KiB
2023-12-13T00:57:57.214670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum227
5-th percentile308.6
Q1598
median1008
Q31397
95-th percentile1671.4
Maximum1739
Range1512
Interquartile range (IQR)799

Descriptive statistics

Standard deviation446.063
Coefficient of variation (CV)0.44522947
Kurtosis-1.277107
Mean1001.8721
Median Absolute Deviation (MAD)397
Skewness-0.049965785
Sum1355533
Variance198972.2
MonotonicityStrictly increasing
2023-12-13T00:57:57.381063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
227 1
 
0.1%
1278 1
 
0.1%
1286 1
 
0.1%
1285 1
 
0.1%
1284 1
 
0.1%
1283 1
 
0.1%
1282 1
 
0.1%
1281 1
 
0.1%
1280 1
 
0.1%
1279 1
 
0.1%
Other values (1343) 1343
99.3%
ValueCountFrequency (%)
227 1
0.1%
228 1
0.1%
229 1
0.1%
230 1
0.1%
238 1
0.1%
239 1
0.1%
240 1
0.1%
241 1
0.1%
242 1
0.1%
244 1
0.1%
ValueCountFrequency (%)
1739 1
0.1%
1738 1
0.1%
1737 1
0.1%
1736 1
0.1%
1735 1
0.1%
1734 1
0.1%
1733 1
0.1%
1732 1
0.1%
1731 1
0.1%
1730 1
0.1%

예약자명
Categorical

Distinct35
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size10.7 KiB
박**
493 
김**
277 
이**
75 
최**
71 
유**
65 
Other values (30)
372 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique8 ?
Unique (%)0.6%

Sample

1st row한**
2nd row김**
3rd row김**
4th row김**
5th row박**

Common Values

ValueCountFrequency (%)
박** 493
36.4%
김** 277
20.5%
이** 75
 
5.5%
최** 71
 
5.2%
유** 65
 
4.8%
한** 52
 
3.8%
류** 50
 
3.7%
정** 40
 
3.0%
장** 39
 
2.9%
과** 38
 
2.8%
Other values (25) 153
 
11.3%

Length

2023-12-13T00:57:57.549337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
박 493
36.4%
김 277
20.5%
이 75
 
5.5%
최 71
 
5.2%
유 65
 
4.8%
한 52
 
3.8%
류 50
 
3.7%
정 40
 
3.0%
장 39
 
2.9%
과 38
 
2.8%
Other values (25) 153
 
11.3%

행사명
Text

Distinct523
Distinct (%)38.7%
Missing0
Missing (%)0.0%
Memory size10.7 KiB
2023-12-13T00:57:57.877102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length38
Mean length11.384331
Min length2

Characters and Unicode

Total characters15403
Distinct characters391
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique399 ?
Unique (%)29.5%

Sample

1st row나노 C&D Lab 초기기업 교육
2nd row지역산업맞춤형 일자리창출사업 수료식-2차
3rd row지역산업맞춤형 일자리창출사업 수료식-3차
4th row지역산업맞춤형 일자리창출사업 수료식-4차
5th row나노STEM K-Girls Day 프로그램
ValueCountFrequency (%)
나노stem 152
 
5.2%
nanostem 140
 
4.8%
연세대학교 114
 
3.9%
교육 113
 
3.9%
과기부 65
 
2.2%
프로그램 57
 
1.9%
나노융합기술인력양성사업 57
 
1.9%
사회공헌 50
 
1.7%
아카데미 45
 
1.5%
교육생 41
 
1.4%
Other values (705) 2097
71.5%
2023-12-13T00:57:58.392478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1657
 
10.8%
교 599
 
3.9%
기 443
 
2.9%
나 418
 
2.7%
육 397
 
2.6%
노 369
 
2.4%
E 348
 
2.3%
M 313
 
2.0%
n 303
 
2.0%
T 300
 
1.9%
Other values (381) 10256
66.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 10200
66.2%
Uppercase Letter 1683
 
10.9%
Space Separator 1657
 
10.8%
Lowercase Letter 1021
 
6.6%
Decimal Number 494
 
3.2%
Close Punctuation 114
 
0.7%
Open Punctuation 114
 
0.7%
Other Punctuation 52
 
0.3%
Dash Punctuation 37
 
0.2%
Connector Punctuation 30
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
교 599
 
5.9%
기 443
 
4.3%
나 418
 
4.1%
육 397
 
3.9%
노 369
 
3.6%
사 239
 
2.3%
회 199
 
2.0%
업 189
 
1.9%
학 181
 
1.8%
연 174
 
1.7%
Other values (309) 6992
68.5%
Uppercase Letter
ValueCountFrequency (%)
E 348
20.7%
M 313
18.6%
T 300
17.8%
S 295
17.5%
C 79
 
4.7%
O 77
 
4.6%
A 57
 
3.4%
P 40
 
2.4%
B 35
 
2.1%
R 21
 
1.2%
Other values (14) 118
 
7.0%
Lowercase Letter
ValueCountFrequency (%)
n 303
29.7%
a 186
18.2%
o 161
15.8%
e 61
 
6.0%
r 49
 
4.8%
t 43
 
4.2%
s 40
 
3.9%
i 35
 
3.4%
m 35
 
3.4%
k 25
 
2.4%
Other values (13) 83
 
8.1%
Decimal Number
ValueCountFrequency (%)
1 124
25.1%
0 118
23.9%
2 109
22.1%
5 30
 
6.1%
9 28
 
5.7%
3 26
 
5.3%
8 21
 
4.3%
6 19
 
3.8%
4 10
 
2.0%
7 9
 
1.8%
Other Punctuation
ValueCountFrequency (%)
. 27
51.9%
& 9
 
17.3%
/ 6
 
11.5%
, 5
 
9.6%
; 2
 
3.8%
: 2
 
3.8%
' 1
 
1.9%
Close Punctuation
ValueCountFrequency (%)
) 96
84.2%
] 18
 
15.8%
Open Punctuation
ValueCountFrequency (%)
( 96
84.2%
[ 18
 
15.8%
Space Separator
ValueCountFrequency (%)
1657
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 37
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 30
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 10200
66.2%
Latin 2704
 
17.6%
Common 2499
 
16.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
교 599
 
5.9%
기 443
 
4.3%
나 418
 
4.1%
육 397
 
3.9%
노 369
 
3.6%
사 239
 
2.3%
회 199
 
2.0%
업 189
 
1.9%
학 181
 
1.8%
연 174
 
1.7%
Other values (309) 6992
68.5%
Latin
ValueCountFrequency (%)
E 348
12.9%
M 313
11.6%
n 303
11.2%
T 300
11.1%
S 295
10.9%
a 186
 
6.9%
o 161
 
6.0%
C 79
 
2.9%
O 77
 
2.8%
e 61
 
2.3%
Other values (37) 581
21.5%
Common
ValueCountFrequency (%)
1657
66.3%
1 124
 
5.0%
0 118
 
4.7%
2 109
 
4.4%
) 96
 
3.8%
( 96
 
3.8%
- 37
 
1.5%
5 30
 
1.2%
_ 30
 
1.2%
9 28
 
1.1%
Other values (15) 174
 
7.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 10199
66.2%
ASCII 5203
33.8%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1657
31.8%
E 348
 
6.7%
M 313
 
6.0%
n 303
 
5.8%
T 300
 
5.8%
S 295
 
5.7%
a 186
 
3.6%
o 161
 
3.1%
1 124
 
2.4%
0 118
 
2.3%
Other values (62) 1398
26.9%
Hangul
ValueCountFrequency (%)
교 599
 
5.9%
기 443
 
4.3%
나 418
 
4.1%
육 397
 
3.9%
노 369
 
3.6%
사 239
 
2.3%
회 199
 
2.0%
업 189
 
1.9%
학 181
 
1.8%
연 174
 
1.7%
Other values (308) 6991
68.5%
Compat Jamo
ValueCountFrequency (%)
ㄴ 1
100.0%

인원수
Real number (ℝ)

Distinct54
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean39.127864
Minimum0
Maximum150
Zeros3
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size12.0 KiB
2023-12-13T00:57:58.596008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile15
Q130
median35
Q340
95-th percentile100
Maximum150
Range150
Interquartile range (IQR)10

Descriptive statistics

Standard deviation22.16294
Coefficient of variation (CV)0.56642346
Kurtosis3.8922334
Mean39.127864
Median Absolute Deviation (MAD)5
Skewness1.8473043
Sum52940
Variance491.19592
MonotonicityNot monotonic
2023-12-13T00:57:58.782604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
40 336
24.8%
30 321
23.7%
20 90
 
6.7%
35 90
 
6.7%
50 82
 
6.1%
100 73
 
5.4%
25 58
 
4.3%
15 52
 
3.8%
60 48
 
3.5%
10 30
 
2.2%
Other values (44) 173
12.8%
ValueCountFrequency (%)
0 3
 
0.2%
1 3
 
0.2%
4 1
 
0.1%
5 5
 
0.4%
6 2
 
0.1%
8 1
 
0.1%
9 2
 
0.1%
10 30
2.2%
12 6
 
0.4%
13 2
 
0.1%
ValueCountFrequency (%)
150 2
 
0.1%
130 5
 
0.4%
120 7
 
0.5%
110 1
 
0.1%
105 4
 
0.3%
100 73
5.4%
90 4
 
0.3%
85 1
 
0.1%
80 17
 
1.3%
75 1
 
0.1%

신청장비명
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size10.7 KiB
<NA>
1144 
낸방기
138 
난방기
 
71

Length

Max length4
Median length4
Mean length3.8455285
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row난방기
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 1144
84.6%
낸방기 138
 
10.2%
난방기 71
 
5.2%

Length

2023-12-13T00:57:58.956783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:57:59.092037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1144
84.6%
낸방기 138
 
10.2%
난방기 71
 
5.2%

예약시작일
Date

Distinct954
Distinct (%)70.5%
Missing0
Missing (%)0.0%
Memory size10.7 KiB
Minimum2017-08-29 00:00:00
Maximum2024-12-03 00:00:00
2023-12-13T00:57:59.241742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:57:59.450536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

예약종료일
Date

Distinct961
Distinct (%)71.0%
Missing0
Missing (%)0.0%
Memory size10.7 KiB
Minimum2017-08-29 00:00:00
Maximum2024-12-03 00:00:00
2023-12-13T00:57:59.627099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:57:59.813412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Interactions

2023-12-13T00:57:56.274399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:57:56.000409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:57:56.435287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:57:56.123800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T00:57:59.926448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대관신청번호예약자명인원수신청장비명
대관신청번호1.0000.7960.5520.478
예약자명0.7961.0000.7170.474
인원수0.5520.7171.0000.077
신청장비명0.4780.4740.0771.000
2023-12-13T00:58:00.036145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
신청장비명예약자명
신청장비명1.0000.397
예약자명0.3971.000
2023-12-13T00:58:00.188932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대관신청번호인원수예약자명신청장비명
대관신청번호1.000-0.2960.4120.477
인원수-0.2961.0000.3810.109
예약자명0.4120.3811.0000.397
신청장비명0.4770.1090.3971.000

Missing values

2023-12-13T00:57:56.944899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T00:57:57.083014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

대관신청번호예약자명행사명인원수신청장비명예약시작일예약종료일
0227한**나노 C&D Lab 초기기업 교육40난방기2017-09-132017-09-13
1228김**지역산업맞춤형 일자리창출사업 수료식-2차20<NA>2017-09-052017-09-05
2229김**지역산업맞춤형 일자리창출사업 수료식-3차20<NA>2017-10-112017-10-11
3230김**지역산업맞춤형 일자리창출사업 수료식-4차20<NA>2017-10-312017-10-31
4238박**나노STEM K-Girls Day 프로그램30<NA>2017-09-082017-09-08
5239박**나노STEM K-Girls Day 프로그램30<NA>2017-09-082017-09-08
6240박**연세대학교리더스포럼최고위과정40<NA>2017-09-042017-09-04
7241박**연세대학교리더스포럼40<NA>2017-09-112017-09-11
8242박**연세대학교40<NA>2017-09-182017-09-18
9244박**연세대학교40<NA>2017-09-252017-09-25
대관신청번호예약자명행사명인원수신청장비명예약시작일예약종료일
13431730황**신규입사자 OT40<NA>2023-09-192023-09-19
13441731이**IMU 시험 분석 보고회20낸방기2023-08-302023-08-30
13451732임**2023년 산업전문인력 AI역량강화교육 재직자과정25<NA>2023-09-072023-09-08
13461733임**2023년 산업전문인력 AI역량강화교육 재직자과정25<NA>2023-09-122023-09-14
13471734김**재직자 위탁교육30<NA>2023-12-072023-12-07
13481735성**10월 월례회의100<NA>2023-10-042023-10-04
13491736박**한국나노기술원 체험 탐방50<NA>2023-10-282023-10-28
13501737김**재직자 위탁교육25난방기2023-12-212023-12-21
13511738박**'23 N-Facility 전체 워크숍80<NA>2023-11-302023-12-01
13521739성**11월 월례회의100<NA>2023-11-012023-11-01